Vagus Nerve Stimulation differentially modulates P3b in responders and non-responders: toward a biomarker of therapeutic efficacy

IntroductionAlthough vagus nerve stimulation (VNS) is an established therapy for drug-resistant epilepsy, its mechanisms of action remain unresolved, resulting in variable clinical efficacy. Given the strong anatomical and functional coupling between vagal afferents and the locus coeruleus–noradrenergic system, this study investigated whether VNS directly impacts an electrophysiological marker of this system, the P3b event-related potential, and how such modulation relates to therapeutic outcomes.MethodsFifteen adults who had undergone long-term VNS implantation performed an auditory oddball task with the device disabled (OFF) and enabled (ON), with ON separated into electrical pulse-train (ON HIGH) and inter-burst break (ON LOW) phases to investigate the direct impact of electrical stimulation on the P3b.ResultsLinear mixed-effects modelling revealed a significant interaction between VNS condition and clinical response: responders showed reduced P3b amplitude (p = 0.023) and prolonged latency during ON (p = 0.007), whereas non-responders exhibited increased amplitude (p = 0.009) and trending shortened latency (p = 0.078). These VNS-induced changes correlated monotonically with a continuous clinical response score (r_amplitude = −0.62, r_latency = 0.48). In addition, a simple classification approach based on a composite amplitude-to-latency index was included to illustrate the potential of P3b modulation as a biomarker for distinguishing responders from non-responders, showing an overall accuracy of 86.7%. No pulse-locked modulation was observed between ON HIGH and ON LOW.DiscussionThese findings demonstrate that VNS elicits group-specific acute effects on cognitive–electrophysiological markers and support P3b modulation as a promising biomarker for predicting therapeutic efficacy.

Brain protein burden is related to intravoxel incoherent motion: PET-MR imaging study

IntroductionDysfunction in brain protein clearance mechanisms is thought to contribute to many neurodegenerative diseases, yet non-invasive assessment of these mechanisms in humans remains challenging. This study is the first to examine whether intravoxel incoherent motion (IVIM) diffusion MRI metrics, measures of water diffusion and fluid dynamics, are associated with pathological protein accumulation and cognition in aging individuals, and hence whether they serve as a proxy for brain waste clearance function.MethodsWe analyzed data from 94 participants (n = 45 β-amyloid positive) who underwent simultaneous PET/MRI scans to calculate three key IVIM metrics: D (true diffusion coefficient), D* (pseudo-diffusion coefficient reflecting perfusion), and f (perfusion fraction) within 98 regions of interest. A machine learning model was trained to identify the most informative IVIM features for predicting β-amyloid (Aβ) status. Selected features were then evaluated for correlations with protein burden (Aβ and tau) and cognitive performance.ResultsThe model identified a subset of 25 key features that effectively predicted Aβ status, achieving a predictive accuracy of 80.0% on unseen data. Regions with important IVIM features aligned with previously identified Aβ-affected regions and showed significant correlations with Aβ burden (r = 0.53, p < 0.0001) and tau burden (r = 0.61, p < 0.0001). A significant negative correlation was observed between IVIM features and cognitive decline (r = −0.60, p < 0.0001). When stratified by Aβ status, this correlation remained significant only in the Aβ-positive group (r = −0.61, p < 0.0001), but not in the Aβ-negative group.ConclusionIVIM-derived metrics (D, D*, and f), which measure water diffusion and perfusion dynamics in the brain, may be valuable non-invasive biomarkers of protein accumulation and associated cognitive decline in the aging human brain.

EEG Biomarkers for ADHD Stimulant Treatment

Conditions: ADHD

Interventions: Drug: methylphenidate HCl; Drug: Mixed amphetamine salts extended release

Sponsors: Boston Children’s Hospital; Seattle Children’s Hospital; Tris Pharma, Inc.

Not yet recruiting

Spatial transcriptomics on an expanded dataset at the brain-electrode interface: exploration of variability and identification of novel biomarkers

The foreign body reaction to implanted electrodes in the brain has long been recognized as a major challenge impacting the performance and reliability of indwelling neurotechnologies. Spatially resolved transcriptomic approaches have enabled high-resolution mapping of cellular and molecular dynamics at the device-tissue interface, yielding novel insight into both acute and chronic tissue responses. Recent whole-transcriptome profiling methods generate exceptionally dense gene expression datasets from individual samples, offering unprecedented resolution and analytical power. Yet, limited studies have explored aggregated results from larger datasets and sample-to-sample variation within an implanted cohort using such techniques due to high costs and complicated downstream analyses. In this work, we provide a comprehensive report of spatial transcriptomics data collected from an expanded cohort of rats (n = 14 rats) implanted with silicon microelectrode arrays in the motor cortices for 1 week (acute) and 6 weeks (chronic). This larger dataset enabled us to explore the variation in results across samples, assess outliers, and examine potential batch effects. We employed differential expression analysis to identify top differentially expressed genes (DEGs) in spatially defined regions at the device-tissue interface to reveal novel biomarkers in the aggregated dataset. We assessed sample-to-sample variabilities, and applied a factorization strategy to identify prominent cell-type contributors of the top DEGs. Using network-based co-expression analysis, we identified gene modules, hub genes, and central regulatory processes governing the device-tissue interface. Our results show: (a) greater variation of top DEGs across samples at the 1-week time point with notable microglial and astroglial cell-type contributors, (b) lower variation of top DEGs across samples and a shift to prominent astroglial cell-type contributors at the 6-week time point, and (c) novel biomarkers that suggest major macrophage- and microglial mediated processes and homeostasis events at the 1-week time point, and greater tissue remodeling, apoptotic and synaptic changes at the 6-week time point. These findings support previous ideas on the evolving tissue response to implanted devices, and present novel details on biomarkers, biological processes and sample variation. Additionally, this study provides a framework for assessing larger datasets employing high-dimensional spatial transcriptomics and highlight key considerations related to across-sample variability and batch effects.

Pioneering Innovation in Transplant Diagnostics

Sara Barrington is CEO of Verici Dx, a precision diagnostics company redefining how transplant clinicians understand and predict graft health. By combining multi-omic analysis with proprietary artificial intelligence (AI) models, Verici Dx delivers predictive, actionable intelligence that helps clinicians optimize therapy, inform biopsy decisions, and stratify risk for complex transplant patients.

In this edition of Asked & Answered, Barrington speaks with Inside Precision Medicine Editor in Chief Damian Doherty about pioneering innovation in transplant diagnostics to better reflect biological and patient complexity, and ultimately, improve health outcomes.

 

Q: Tell me about Verici Dx, its founding, mission, and products.

Sara Barrington: Verici Dx was founded with a very clear purpose: to fundamentally improve how transplant clinicians are informed and manage graft health. Transplant medicine requires high-stakes, time-sensitive decision-making to promote longevity of the graft, minimize the risk of complications, and improve the patient’s quality of life.

Sara Barrington
Sara Barrington

Kidney transplantation has long struggled with one fundamental challenge: accurately identifying rejection early and distinguishing it from other causes of injury and graft dysfunction. Clinicians often rely on conventional blood markers such as serum creatinine or, more recently, donor-derived cell-free DNA. While these tools are useful for signaling that “something is wrong,” they are injury markers and lack a level of precision important in rejection biology.

Creatinine levels, for example, increase only after functional damage has already occurred and cannot differentiate rejection from non-immune causes of injury such as ischemic reperfusion injury, drug toxicity, or viral infections like BK virus–associated nephropathy. Biomarkers can generate false positives, triggering biopsies or treatment escalation that may not be necessary and can expose patients to avoidable risk.

This lack of specificity has made rejection difficult to manage proactively. By the time rejection is clearly identified, tissue injury may already be established. At the same time, clinicians are understandably cautious about intensifying immunosuppression without clear evidence, given the associated risks of infection, malignancy, and toxicity.

Our mission is to close this information gap by delivering precision diagnostics that reflect the true complexity of transplant biology and translate that complexity into insights clinicians can proactively and confidently apply to patient care.

We operate at the intersection of multi-omic science, advanced analytics, and clinical reality. We know that transplant rejection and graft injury are not single-signal events, but are multifactorial, dynamic biological processes. We design our diagnostics to capture that complex biology in a way that mirrors how clinicians think about their patients, rather than forcing clinical decision-making to fit the limitations of older technologies.

Our lead product, Tutivia™, is a blood-based test that assesses the immune and broader, relevant biological status of kidney transplant patients to identify the risk of all forms of acute rejection, including T cell (TCMR) and antibody-mediated rejection (ABMR). Tutivia combines transcriptomics with proprietary AI models to address this precise unmet need: biologically accurate insight into what is actually happening within the graft.

The test delivers a risk score that enables more precise immunosuppression management by distinguishing rejection from other causes of graft injury, such as BK virus–associated nephropathy and ischemia-reperfusion injury, which can confound conventional blood tests like serum creatinine and donor-derived cell-free DNA.

By focusing on the immune and other pathways associated with rejection, Tutivia moves beyond damage markers and toward a direct assessment of rejection biology itself. That shift, from injury detection to biological interpretation, is what makes the test such a valuable tool for transplant clinicians.

Thermo Fisher Scientific recently launched its One Lambda™ Pre-Transplant Risk Assessment (PTRA) assay, using pre-transplant prognostic technology licensed from Verici Dx. The assay provides a risk score for early acute rejection based on a patient’s unique gene profile, helping clinicians better balance the risk of rejection against the potential side effects of over-immunosuppression. Using a 29-gene mRNA signature, the PTRA assay stratifies patients into high- and low-risk categories, with clinical validation showing high-risk patients are seven times more likely to experience early acute rejection.

 

Q: Tutivia is built on RNA sequencing. Why is precision transcriptomic analysis well-suited for identifying rejection biology?

Barrington: The need for reliable biomarkers is crucial for individualizing therapy that offers the potential to extend allograft survival.

Early research underpinning the science leading to the development of Tutivia was led by principal investigators at The Mount Sinai Hospital in New York, one of the world’s leading transplant research centers, combining decades of clinical expertise with rigorous science. The underlying science reflects the fact that rejection in kidney transplant patients is not driven by a single molecule or pathway, it results from coordinated immune and other biologic pathways across multiple cell types, signaling cascades, and regulatory mechanisms. Injury-driven biomarkers capture only a narrow slice of this biology and can be influenced by non-rejection factors, limiting their specificity and reliability.

Precision transcriptomic analysis, on the other hand, measures gene expression patterns across thousands of genes simultaneously. In developing specific tests, this analysis is the basis for gene selection using unsupervised deep learning mathematical modeling, allowing the most impactful and reproducible gene expression signals and interactions to be included in the final signature.

Tutivia uses a peripheral blood next-generation sequencing assay to evaluate a 17-gene mRNA signature in combination with a proprietary artificial intelligence algorithm to categorize kidney transplant patients as at low risk or high risk of acute rejection.

This provides a comprehensive view of immune activation, regulation, and injury responses within the transplanted organ, allowing the identification of signature changes that are truly characteristic of rejection biology.

In short, RNA sequencing lets us ask better biological questions: not just whether the kidney is injured, but whether immune-mediated rejection is driving that injury. That distinction is critical for precision medicine in transplantation.

 

Q: What does earlier and more precise identification of rejection biology mean for patient management and outcomes?

Barrington: Earlier identification of rejection biology can create an opportunity to intervene before irreversible damage occurs. When clinicians have confidence in what the biology is telling them, they can make timely, targeted decisions that may preserve graft function.

This precision also supports more individualized care. Rather than applying broad treatment strategies, clinicians can tailor immunosuppression based on biological risk, potentially reducing over-treatment and its associated complications.

For patients, this can translate into fewer unnecessary biopsies, fewer adverse events related to immunosuppression, and a greater likelihood of long-term graft survival. Ultimately, better information leads to better decisions, and better decisions lead to better outcomes.

Our vision is that precision diagnostics like Tutivia become a standard component of transplant management, providing earlier insight into rejection biology, supporting more informed clinical decisions, and helping clinicians intervene at the right time for the right patient.

 

Q: AI is central to your platform. How does Verici Dx apply AI differently from others in diagnostics?

Barrington: We apply AI with rigor and restraint. We use advanced machine learning and mathematical modeling to analyze highly complex biological data, but always within a disciplined scientific framework. Our models are developed using unsupervised approaches and validated extensively on inclusive patient populations. Once validated, they are locked and reproducible; they are not evolving over time. That distinction matters because clinicians are making life-altering decisions based on these results, and trust, consistency, and validation are essential.

 

Q: Validation and standards are recurring themes for Verici Dx. How was Tutivia validated?

Barrington: Tutivia was validated through a rigorous clinical study that included a broad and diverse transplant patient population, rather than narrowly curated cohorts. We deliberately chose a more difficult validation path because clinical reality is complex, and diagnostics must perform under those conditions. While this approach requires more time and effort, it ensures the test is reliable, reproducible, and clinically relevant across the full spectrum of patients that clinicians see every day.

 

Q: What’s in the future for the company?

Barrington: Verici Dx is focused on deepening the clinical adoption of Tutivia as well as expanding the studies demonstrating the utility of an earlier and more precise biomarker in improving patient outcomes. Long-term outcomes for transplant patients involve more biological pathways, and significant complexity is involved in managing care. We are focused on developing and validating tests using both transcriptomic and proteomic precision tools to assist clinicians and their patients in this journey.

 

Damian Doherty has been in media and publishing for over 30 years, beginning at News Corporation. Damian has managed, edited, and launched life science titles in drug discovery and precision medicine. He was features editor of Drug Discovery World and founded the Precision Medicine Leaders Summit and the Journal of Precision Medicine. He edited AIMed magazine before launching Photo51Media, a platform for illuminating untold, compelling stories in precision healthcare. Damian joined Mary Ann Liebert in 2021 to help steer the new rebrand and relaunch of Clinical OMICS to Inside Precision Medicine.

The post Pioneering Innovation in Transplant Diagnostics appeared first on Inside Precision Medicine.

Stopping Neurodegeneration in Place with Vaccines

Developing truly disease-changing treatments for Alzheimer’s disease and other neurodegenerative conditions has proved challenging, with many failed trials over the last few decades. The approval of Eisai/Biogen’s monoclonal antibody lecanemab in 2023, the first such treatment to have a positive, albeit modest, impact on symptoms of Alzheimer’s disease, was therefore received with enthusiasm by many.

Critics of lecanemab and Eli Lilly’s donanemab, approved a year later for the same indication, argue that the small benefit gained from the drugs does not outweigh the economic costs, possible side effects, and burden of regular intravenous infusions.

Using a vaccine-style approach, where the treatment prompts the body to generate its own antibodies, has the potential to solve these problems. Several companies are developing active immunotherapies to target Alzheimer’s and Parkinson’s disease, as well as other neurological conditions.

Andrea Pfiefer
Andrea Pfiefer, PhD
CEO and Co-founder
AC Immune

“What we’re trying to do is link the antigen to a carrier and bring it into a form which mimics the pathology,” explained Andrea Pfeifer, PhD, CEO and co-founder of Swiss company AC Immune, a leading biotech taking the active immunotherapy route to target Alzheimer’s and Parkinson’s disease.

“We inject it into the immune system, and what it recognizes is the misfolded protein. So, because of that, the immune system only makes antibodies against this pathological protein.”

Although none have yet reached the market, the active vaccine-style approach potentially has a number of advantages over passive treatment with monoclonal antibodies. Importantly, fewer rounds of treatment are required. The exact dosing is yet to be determined, but it would certainly be less frequent than the regular infusions of lecanemab or donanemab that are currently prescribed. This would help reduce costs and treatment burdens for patients and their families. There is also likely to be less risk of amyloid-related imaging abnormalities (ARIA) due to the relatively slower onset of antibody generation by the body.

“If you have to take the patient every two to four weeks to get a two-hour infusion in a hospital, and then you have to wait and do imaging, it’s really burdensome,” said Pfeifer.

“After a certain while, they just don’t want to go. … They say, ‘Sorry, we believe your science, we believe everything, but we don’t want this.”

To date, most vaccine trials have enrolled people with at least some degree of Alzheimer’s or Parkinson’s disease, as preventive vaccine trials need to be large and long in duration. Theoretically, developing a preventive vaccine is a feasible approach, as many neurodegenerative diseases typically have a slow onset before noticeable symptoms appear. However, reliable biomarkers that can accurately predict disease onset have been in short supply.

Alzinova’s ALZ-101
ALZ-101 – Alzinova’s disease-modifying vaccine candidate for Alzheimer’s disease

This is changing, though. Last year, two blood tests that measure phosphorylated tau and amyloid ratios were approved by the U.S. Food and Drug Administration (FDA) for Alzheimer’s diagnosis. The biomarker field is less developed for Parkinson’s and other neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS), but things are slowly improving.

Promising mid-stage results from front-runners like AC Immune and Alzinova suggest that this pathway has merit, but whether they can succeed in larger registrational trials going forward is unclear.

Tord Labuda
Tord Labuda, PhD
CEO, Alzinova

“It remains to be seen how our immune system reacts. I think that when we look at the titers we see from the vaccine, they’re similar to what we get with passive immunizations. So I think there are a lot of things that point in the right direction,” said Tord Labuda, PhD, CEO of Swedish biotech Alzinova, which has an amyloid beta vaccine in development.

“Personally, I don’t think that the vaccine or passive immunization is the real challenge. The real challenge is to have the right target.”

Taking a more active approach to immunotherapy

While passive immunotherapies like lecanemab and donanemab are groundbreaking in that they are the first disease-modifying treatments for Alzheimer’s to be approved by the FDA and they slow cognitive decline by around 25%–35% over two years, these drugs can cause significant side effects such as ARIA.

This can cause brain swelling and bleeding in some people. Individuals at highest risk for some neurodegenerative conditions, such as carriers of the APOE4 gene variant, are prevented from accessing these therapies at all, as they have a higher-than-average risk of experiencing ARIA-like side effects.

Treating neurodegenerative diseases like Alzheimer’s and Parkinson’s disease when symptoms commence is problematic, as currently, there is no known method of regaining neuronal function once it has been lost.

Classic pathology studies suggest that, by the time the typical motor symptoms of Parkinson’s appear, around 50%–70% of dopaminergic neurons are already lost from the brain. Similarly, in early clinical Alzheimer’s disease, where those affected have mild dementia, hippocampal volume in the brain seen on imaging is already up to 25% lower than that of age-matched controls. This means, however good the treatment is, the patients will never regain complete function.

“There’s no way we can restore these neurons,” said Roman Kniazev, CEO of U.S.-biotech Nuravax, which is developing several different Alzheimer’s vaccines. “They are gone forever. So that is why the best strategy, and this is our motto in our company, is to not let the pathology kill the neurons.”

Researchers trying to develop new therapies for Alzheimer’s and Parkinson’s are increasingly moving towards an early or even preventive approach. The idea of a vaccine-like approach to targeting Alzheimer’s is not new. Animal work in the late 1990s showed that vaccinating against amyloid‑beta could clear plaques and improve cognition in transgenic mouse models. This led to the development of Elan/Wyeth’s amyloid‑beta vaccine, AN1792.

It entered Phase I/II trials for mild‑to‑moderate Alzheimer’s and successfully induced anti‑amyloid beta antibodies in some patients. But the study had to be stopped in 2002 because around six percent of the participants developed meningoencephalitis, linked to T cell–mediated inflammation in the brain. Despite strong amyloid plaque clearance, there was little impact on symptoms in the clinical trial participants.

Several other candidates, designed to avoid the T-cell activation seen with AN1792, have been unsuccessfully trialed over the last two decades. Although largely safe and antibody-producing, most of these programs were discontinued due to a lack of efficacy.

The field has persevered despite this, with improvements in technology, safety, biomarkers, and clinical trial design having led to a new generation of vaccine candidates that, while not yet approved, are showing good results in Phase I and II trials.

Neil Warma
Neil Warma
CEO, ProMIS Neurosciences

“I think what we’ve learned over the past five or 10 years from other vaccine approaches is that the next generation are those that come with a very precise approach to generating antibodies against the toxic species of a given protein for that specific neurodegenerative disease,” said Neil Warma, CEO of ProMIS Neurosciences, a U.S.-based company taking an antibody and a vaccine-based approach to treating Alzheimer’s and other neurodegenerative diseases.

“Those are really the things that make the vaccine approach much more interesting now. The sophistication of the biomarkers, the data we’ve learned from past and current products in the market, and then this ability to design and create antibodies that are highly specific to a targeted pathogenic form of the protein.”

AC Immune has three active immunotherapy candidates in Phase II: an anti-amyloid beta therapy, ACI-24, that is being developed with Takeda; an anti-tau therapy, ACF 35, being developed with Johnson & Johnson; and an anti-alpha synuclein candidate targeting Parkinson’s disease.

Staining of neurons in the brain
Staining of neurons in the brain from Neil Cashman’s lab-1.

The company reported good results for its Parkinson’s Phase II study at the end of last year. The interim study results showed a 100% response rate and a good safety profile in people with early Parkinson’s disease. Alpha-synuclein and neurofilament light levels in the blood, as well as scores from standard movement tests, suggested that disease stabilization had occurred.

If confirmed by results from the second part of the study, this would be the first time that disease modification, rather than symptom management, has shown promise for Parkinson’s disease. It would also confirm alpha synuclein as a pathogenic contributor to the condition.

“The statistical variability was very, very small, which was a surprise to us. Every single marker, preclinical biomarker, clinical imaging, went into the same direction,” said Pfeifer. “For me, what was particularly rewarding was that there was a connection between the titers, so the antibody response in the people versus the reduction of this pathology … the alpha-synuclein versus the imaging, which showed that the neurons can be protected.”

Better targeting to improve safety and efficacy

A common theme among vaccine developers in the neurodegeneration space is precision targeting. There is a strong consensus that a lack of specificity when picking targets is likely why many trials failed to show efficacy and had significant side effect issues in the past.

Different companies or research groups back slightly different protein targets, but the experts all emphasize the importance of avoiding binding to inert plaque in the brain in Alzheimer’s disease, and of targeting toxic, misfolded proteins that are disease-specific.

“We provide the body with active immunotherapy, and then the body induces the antibodies. But what is important is that these antibodies are really specific for the pathological form,” said Pfeifer.

AC Immune is not the only company with a keen focus on tightening up targeting in this area. Alzinova is specifically targeting toxic amyloid beta oligomers with its lead candidate ALZ-101, a therapeutic Alzheimer’s vaccine.

It received a recent FDA Fast Track designation for ALZ-101 after good safety and efficacy data were reported last year from its completed Phase Ib clinical trial.

“They have shown in many in vitro and in vivo models that … when you remove these toxic oligomers using antibodies towards them, you can basically neutralize the toxicity in these extracts towards the neurons,” explained Labuda.

He added that many of the “vaccines, as well as the monoclonal antibodies, are going for the N-terminal part of the protein. … By doing that, you will target the monomers, all the fibrils, but most importantly, also the plaques. Very little will be left to bind to something else that might be more important for the disease. I think this is what we see with the current treatments on the market. There’s a lot of off-target effects … and that’s why we have these huge challenges.”

ProMIS is also targeting amyloid beta oligomers in Alzheimer’s using both a monoclonal antibody and vaccine approach. It has developed a special method with the help of artificial intelligence to develop antibodies, taking both conformational shape and protein sequence into account.

“These three-dimensional shapes don’t exist on monomers, and they’re buried in plaque. We’ve tried and tried and tried to get these antibodies to bind monomers, to bind plaque, and they really don’t, which is good,” said Warma.

“We’ve done side-by-side testing with other antibodies to see if ours is truly differentiated. … In many different studies before we got to the clinic, PMN-310, our therapeutic antibody, was the only one that bound oligomers and avoided monomers and plaque. All the others cross-reacted with everything.”

ProMIS is testing its PMN-310 antibody before moving on to the vaccine approach. “If we can come with that one-two punch to say we’ve got a drug now that can treat patients with Alzheimer’s, we’ve got the ability to detect the onset of disease pathology in Alzheimer’s, and we have a vaccine that prevents you from developing that disease, I mean, that would be a pretty powerful combination,” noted Warma.

Nuravax is aiming to address two key shortcomings of first‑generation Alzheimer’s vaccines, such as AN1792: the risk of problematic T cell-driven inflammation and uneven immune responses in older adults. Its MultiTEP‑based candidates (AV‑1959R, AV‑1980R, and Duvax) are engineered to elicit a strong, antibody‑dominant response against amyloid‑beta and tau while minimizing activation of potentially autoreactive T cells and maintaining effectiveness.

“The platform which we developed makes the vaccine highly immunogenic, and this high immunogenic feature is essential for diseases in the brain,” said Kniazev.

Kiran Bhaskar
Kiran Bhaskar, PhD
Professor
University of New Mexico

Kiran Bhaskar, PhD, is a professor and group leader at the University of New Mexico. He has worked on Alzheimer’s disease for many years and is also a scientific co-founder of TheraVac Biologics. He and his colleagues are developing an anti-tau Alzheimer’s vaccine that is about to start human trials.

They are also aiming to reduce risks associated with immune reactions to vaccine adjuvants, which can contribute to ARIA, and have created a vaccine that does not need an adjuvant.

“We use a strategy called a virus-like particle,” he explained. “You don’t need to expect any side effects because of adjuvants. In this way, we trick the immune system into thinking that there is a viral attack on the body. It immediately starts an immune response against the virus-like particle and also anything sticking to the surface of those virus-like particles, which in this case is pathological or phosphorylated tau proteins.”

Overall, in the trials carried out so far in the active immune therapy space in Alzheimer’s disease, rates of ARIA have been very low, which is another selling point for the vaccine approach. “We don’t expect to see ARIA in active immunotherapy because we are using the host’s own immune response system to generate antibodies. … So that way there’ll be less unanticipated immune response,” explained Bhaskar.

syringe and vaccine bottle
Credit: Ake Ngiamsanguan / iStock / Getty Images Plus

Overcoming challenges on the road to the clinic

There is no doubt that active immunotherapies or vaccines to target Alzheimer’s and Parkinson’s disease are more advanced than they have ever been before, but they are still a long way from a mainstream rollout.

One reason the conversation has shifted is that the approval and broader use of the first anti-amyloid antibodies, for all their modest effect sizes and ARIA issues, shows that lowering the right protein species can slow deterioration. Using a more vaccine-like approach, where people make their own antibodies, does have the potential to make targeting these conditions safer, cheaper, and more accessible for patients.

But basic clinical questions remain unanswered. For example, how long vaccine-induced protection will last, how often boosters will be needed, and whether early stabilization of biomarkers and motor or cognitive scores—such as AC Immune’s interim Parkinson’s data or Alzinova’s Phase Ib Alzheimer’s study results—will translate into true preserved function a decade later.

Biomarkers are a big potential stumbling block for the development of preventive vaccines. The position is better for Alzheimer’s disease; the FDA’s approval of two blood-based Alzheimer’s biomarkers now gives developers a way to find people with silent pathologies without relying solely on positron emission tomography imaging. But there is still a lot more to do on this front, particularly in diseases like Parkinson’s, ALS, or other neurological or neurodegenerative diseases where less is known.

surgical glove pointing at a brain scan image
Credit: Martin Philip / iStock / Getty Images Plus

“We need better and safer treatments, but it’s also linked to having the right biomarkers, because if you have a risk factor, it doesn’t mean necessarily that you have the disease,” said Pfeifer. “These biomarkers are still not very well established. … The goal is absolutely to go to preclinical, and preclinical will require these biomarkers. If you ask me what is needed most in Parkinson’s right now, [it] is definitely to have better biomarkers.”

A second stumbling block for companies that want to develop vaccines that can effectively immunize people against neurodegenerative disease is that clinical trials of vaccines in populations of people with no symptoms have historically been large, expensive, and time-consuming—something out of reach of most biotechs without significant outside investment.

ProMIS and others are hoping that the efficacy of their therapeutic antibodies will boost their vaccine pipeline in the future. “If we show that it works in Alzheimer’s, then a similar approach should work in these other diseases,” said Warma. “Since it’s an almost identical process for vaccines, it also shows proof of concept for this whole wave of vaccines coming behind it.”

For now, active immunotherapies promise something that is more modest than true disease prevention but still crucially important. Namely, cheaper, less burdensome, and potentially safer ways to target the same disease biology as today’s monoclonal antibodies, ideally years earlier in the process.

The post Stopping Neurodegeneration in Place with Vaccines appeared first on Inside Precision Medicine.

Lipid-Protein Biomarker Makes Clinical Debut with Early Ovarian Cancer Detection

For Anna Jeter, the story behind AOA Dx’s promising ovarian cancer diagnostic begins with a misconception. Despite serving more than half the population, women’s health continues to be viewed by many investors as a niche category—an assumption Jeter believes has contributed to decades of underinvestment in some of medicine’s most pressing unmet needs. 

“Whenever you speak to investors about women’s health, there’s this perception that it’s somehow a smaller market,” Jeter, co-founder and chief regulatory officer of AOA Dx, told Inside Precision Medicine. “Women represent 51% of the population, but historically women’s health has been treated as a specialty category rather than a major healthcare market.” 

That perception has shaped innovation patterns across healthcare, particularly in diagnostics. Despite advances in genomics, liquid biopsy, and AI in oncology, ovarian cancer detection has stagnated. The biomarker Cancer Antigen 125 (CA-125), introduced in 1987, remains the primary blood-based tool used to evaluate women presenting with symptoms suggestive of ovarian malignancy. 

“There have been very few advancements in ovarian cancer,” Jeter said. “The standard of care today is still largely based on technology that became available almost 40 years ago.” 

Early detection could have massive, life-changing consequences, as ovarian cancer is often highly treatable when diagnosed early. More than 90% of women survive when the disease is identified at stage 1, yet nearly 80% of cases are diagnosed only after the cancer has progressed to advanced stages. 

After more than 15 years of developing diagnostics companies centered around women’s health, Jeter, Oriana Papin-Zoghbi, and Alex Fischer decided to take action and co-founded AOA Dx. Through an early partnership with McGill University, the team began investigating whether emerging advances in multi-omics could uncover biological signals that existing ovarian cancer diagnostics were missing. 

Anna Jeter AOA Dx
Anna Jeter, co-founder and chief regulatory officer of AOA Dx

AOA Dx recently announced that its investigational blood test, AKRIVIS GD, achieved 92% sensitivity for Stage I and II ovarian cancer detection in symptomatic women—nearly double the sensitivity historically associated with CA-125 alone. 

Yet Jeter argues the most important aspect of the findings is not the performance metric itself, but what enabled it: the successful translation of lipid biomarkers into a clinical oncology assay. “We are now looking at lipids as very specific biomarkers, which have made a major impact on our ability to detect ovarian cancer significantly earlier,” she said. “And we believe this approach can be translated into other cancers in the future.” 

In fact, it may even go beyond that, as the most notable multi-omic approaches using lipidomics and proteins, such as recent work for stratifying Alzheimer’s disease subtypes, are still in early research phases. 

Blood-based tests beyond DNA 

The announcement, which was recently made at the 2026 American Society of Clinical Oncology (ASCO) annual meeting, reflects a growing shift within cancer diagnostics away from single-analyte approaches and toward integrated biological modeling. Over the past decade, liquid biopsy innovation has largely centered on circulating tumor DNA (ctDNA), driven by advances in next-generation sequencing and the promise of minimally invasive genomic profiling. However, ctDNA performance has varied substantially across tumor types and disease stages, particularly in malignancies characterized by low tumor shedding during early progression. 

Jeter contends that ovarian cancer exemplifies these limitations. “Certain cancers shed ctDNA very effectively into circulation, and in those cases the technology performs very well,” Jeter said. “But in other cancers, either the shedding is insufficient for the sensitivity required at early stages, or the specificity profile becomes challenging. That has led to a broader realization across the field that a single biological layer cannot fully capture disease progression.” 

Increasingly, oncology researchers are converging around multi-omic frameworks that integrate orthogonal biological signals, including proteomic, metabolic, genomic, and transcriptomic features. Within that context, lipid metabolism has emerged as an area of renewed interest. 

Lipid signaling, long associated primarily with cardiovascular disease and metabolic disorders, now plays a deeply intertwined role in oncogenesis. Alterations in lipid metabolism contribute to membrane remodeling, inflammatory signaling, tumor proliferation, immune modulation, and metastatic adaptation. Tumors frequently undergo profound metabolic reprogramming early in disease development, creating detectable shifts in circulating lipid and metabolite profiles before conventional biomarkers become clinically informative. 

“What we have learned is that lipid metabolism appears to be highly active in the earliest stages of disease,” Jeter said. “That biology has been described in the literature for some time. The challenge has been translating those discoveries into a clinical-grade diagnostic assay.” 

That translation problem is nontrivial. Lipids present substantial analytical complexity due to structural diversity, isomeric overlap, and variability in sample handling and quantitation. Discovery-level lipidomics frequently produces promising signals that prove difficult to standardize under regulated clinical laboratory conditions. AOA Dx’s central claim is that it has successfully navigated that transition. 

The company’s platform integrates targeted lipidomic and metabolomic profiling using high-resolution mass spectrometry with protein biomarker analysis via immunoassays. Machine-learning models are then applied to derive composite signatures associated with ovarian malignancy. 

New clinical biomarker class 

According to the company, the assay was developed through biomarker discovery efforts involving more than 2,200 patient samples across multiple cohorts and demographic populations. 

Importantly, the ASCO dataset focused specifically on the intended-use population: symptomatic women presenting in routine clinical settings with nonspecific but concerning symptoms such as abdominal pain, bloating, urinary changes, or altered bowel habits. 

That population reflects a longstanding clinical challenge in gynecologic oncology. Although the majority of ovarian cancer patients report symptoms beginning relatively early in disease progression, those symptoms are often diffuse and overlap extensively with benign gastrointestinal or genitourinary conditions. As a result, diagnostic delays remain common, with patients frequently cycling through multiple evaluations before referral to gynecologic oncology. 

“About 85–95% of women begin experiencing symptoms as early as stage 1,” Jeter noted. “But the symptoms are nonspecific enough that providers often do not initially suspect ovarian cancer.” 

As a result, nearly 80% of ovarian cancers are still diagnosed at advanced stages, despite the dramatic survival differential associated with early intervention. When detected at stage 1 or 2, five-year survival rates exceed 90%. Once metastatic dissemination occurs, however, outcomes deteriorate sharply. 

The company’s results suggest that multi-omic integration may provide clinically meaningful improvements over historical CA-125 performance, particularly in early-stage disease where existing diagnostic sensitivity has remained inadequate. According to AOA Dx, AKRIVIS GD achieved nearly double the early-stage sensitivity historically associated with CA-125 alone. 

The broader implication is not simply improved biomarker performance but a reframing of how cancer detection may evolve over the next decade. Rather than relying on single molecular features, next-generation diagnostics are increasingly attempting to model disease as a systems-level biological phenomenon. 

“There’s a growing recognition that different biological pathways become informative at different stages of disease progression,” Jeter explained. “Some protein markers rise later. Some genomic signals are difficult to detect early. By integrating lipidomic, metabolomic, and proteomic information simultaneously, we’re able to observe the disease from multiple biological angles.” 

The company describes this infrastructure as a broader discovery engine known as GlycoLocate, which is designed to interrogate thousands of lipid and metabolite signatures across multiple disease states. Ovarian cancer represents the company’s first targeted clinical application, but executives indicate the platform is already being expanded into additional oncology indications, particularly within women’s health. 

The women’s health investment gap 

AOA Dx’s emergence also reflects a broader maturation within women’s health biotechnology, a sector that historically struggled to attract sustained institutional investment despite its substantial market opportunity. 

Jeter has spoken openly about what she views as a longstanding disconnect between investor perception and commercial reality in women’s health innovation. Earlier this year, she presented an investment analysis at the 2026 JP Morgan Healthcare Conference examining historical returns within the category. 

“Women’s health has traditionally been viewed as a niche market, despite women representing more than half the population,” she said. “Part of the issue is that many successful companies serving women have not historically been classified as women’s health investments, so the return profile of the sector has been systematically underestimated.” 

That dynamic may now be shifting as women’s health increasingly intersects with other high-growth sectors, including artificial intelligence, precision medicine, molecular diagnostics, and computational biology. AOA Dx itself sits squarely at that convergence point, combining AI-driven biomarker modeling with high-complexity laboratory diagnostics and oncology applications. 

The company is now advancing AKRIVIS GD toward validation studies and an early-access launch program. Equally important will be demonstrating clinical utility and securing reimbursement pathways, both of which remain major barriers for emerging diagnostics platforms. “It’s one thing to develop a test,” Jeter said. “It’s another thing entirely to ensure that patients can actually access it through reimbursement and coverage.” 

To support commercialization efforts, AOA Dx has expanded its leadership team with executives experienced in diagnostic platform deployment and LC-MS assay translation, including chief product officer, Chris Roberts, and senior director of biomarker and analytical development, Cory Bystrom, PhD. 

Whether lipidomics ultimately becomes a foundational pillar of oncology diagnostics remains uncertain. However, the field appears to be entering a transitional period in which metabolic biology is moving from peripheral exploratory science toward regulated clinical application. 

For AOA Dx, the ambition extends beyond ovarian cancer itself. The company sees lipid-based multi-omics as an entirely new diagnostic layer capable of complementing—and in some settings potentially surpassing—the limitations of genomics-only approaches. “What I often say,” Jeter reflected, “is that the situation feels very similar to where next-generation sequencing was 10 or 15 years ago.” 

If the company’s early data continues to hold in larger validation cohorts, AOA Dx may not simply be introducing another ovarian cancer assay. It may help to define the next biological frontier of liquid biopsy diagnostics. 

The post Lipid-Protein Biomarker Makes Clinical Debut with Early Ovarian Cancer Detection appeared first on Inside Precision Medicine.

The exercise-microbiota-queuine-tRNA axis in Parkinson’s disease: evidence, uncertainties, and experimental priorities

Parkinson’s disease (PD) is a multisystem neurodegenerative disorder characterized by progressive nigrostriatal dopaminergic degeneration, α-synuclein aggregation, mitochondrial dysfunction, oxidative stress, and neuroinflammatory remodeling. Although these mechanisms have been extensively investigated, how systemic metabolic and microbiota-derived signals intersect with neuronal translational control remains incompletely understood. Queuosine (Q) modification of tRNAs is a distinctive RNA modification because its precursor, queuine, is not synthesized de novo by mammalian cells but is acquired from diet and gut microbial metabolism. Emerging evidence indicates that Q-tRNA modification can influence codon decoding, translational speed, proteostasis, oxidative stress responses, and mitochondrial function, but direct evidence linking Q-tRNA dysregulation to PD remains limited. In this narrative review, we propose a conceptual and hypothesis-generating framework in which the microbiota-queuine-Q-tRNA modification axis may contribute to neuronal translational buffering and stress adaptation in PD. We distinguish established mechanisms, emerging evidence, and speculative links, emphasizing that the complete causal chain from exercise-induced microbiota remodeling to altered queuine availability, Q-tRNA modification, mitochondrial translational recalibration, and dopaminergic neuroprotection has not yet been experimentally demonstrated. We further discuss tRNA-derived fragments (tRFs) as candidate biomarkers and potential effector molecules in PD-associated translational stress, neuroinflammation, and intercellular RNA communication. Finally, we outline experimental priorities for validating this model, including direct Q-tRNA profiling in PD tissues and biofluids, exercise-intervention studies in PD models, microbiota/queuine manipulation, and mechanistic testing of circulating RNA carrier transport across the blood-brain barrier. This framework does not establish a new pathogenic pathway, but provides a structured roadmap for investigating how exercise, microbial metabolism, and RNA modification biology may converge on selective neuronal vulnerability in PD.